Image segmentation in obstetrics and gynecology.
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Algorithms↗
Biomedical subjects
S Akselrod
Publications and source records attributed to S Akselrod.
Spectral analysis of left ventricular area variability as a tool to improve the understanding of cardiac autonomic control.
Spectral analysis of the fluctuations in heart rate (HR) or blood pressure (BP) has been extensively used as a tool for the noninvasive assessment of autonomic control of the heart. The recently developed echocardiographic acoustic quantification allows noninvasive continuous measurement of the left ventricular cross-sectional area (LVA) signal. In this study, we investigated whether the LVA signal, and more specifically its fluctuations, can be reliably subjected to spectral analysis, and whether the results of such analysis may improve the understanding of the cardiovascular control mechanisms. Our results show that the general pattern of power spectra of LVA fluctuations, as well as their reproducibility, is similar to the power spectra of HR and BP fluctuations. Analysis of LVA signals obtained in normal subjects at rest as well as under vagal blockade and under held respiration, and in patients with known autonomic dysfunction, showed significant differences between groups and states. The effects of age, related to the reduction in parasympathetic activity, were not evident in the spectral content of the LVA and BP signals. The high frequency LVA fluctuations are mainly of mechanical origin, since they were eliminated by breath-holding. We observed an increase in the high frequency LVA fluctuations under vagal blockade, indicating that under normal (control) conditions, these high frequency fluctuations are attenuated by parasympathetic activity. The enhancement in high frequency fluctuations in LVA observed in diabetic patients can thus be attributed to reduced parasympathetic activity. The analysis of LVA variability may be used as a tool for basic research and, possibly, as a quantitative clinical measure for specific disease states.
Adolescent↗
A simulation of the SA node by a phase response curve-based model of a two-dimensional pacemaker cells array.
This paper presents a simulation of the sino-atrial (SA) node by a two-dimensional pacemaker cells array model, based on phase response curve (PRC) interaction. This simple model of the cardiac pacemaker cells, involves only the most basic functional properties, which play a direct role in the determination of the SA node rhythm. The two most relevant functional properties of the pacemaker cells are: The intrinsic cycle length, an "internal" feature of each pacemaker cell, and the PRC, an "overall collective" function. The PRC contains the "information" about the type of interactions of each pacemaker cell with the outside world (i.e., interaction with neighboring cells, external stimulus, etc.), and "strength" of the interaction (strong, weak, etc.). We studied the spatial interaction among a large number of pacemaker cells (15 x 15), as a function of the regional variation of cells properties, the "electrical" coupling between cells (the PRC), and the appearance of regions with abnormal cycle lengths. We investigated the influence of those parameters on the mutual interaction between the pacemaker cells, on the activation pattern and conduction time of the array, and on a pseudo-electrocardioigram (ECG) signal. This study demonstrates that by representing the pacemaker cells in the SA node by only two fundamental features, and by applying a simple physical-mathematical model, we can create a global picture of the SA node system. This enables us to explore physiological phenomena related to the genesis and maintenance of the SA node activity, and to gain insight into the conditions which predispose the SA node instability, and conduction disturbances.
Body Surface Potential Mapping↗
Bifurcation in a simple model of the cardiovascular system.
A simple nonlinear beat-to-beat model of the human cardiovascular system has been studied. The model, introduced by DeBoer et al. was a simplified linearized version. We present a modified model which allows to investigate the nonlinear dynamics of the cardiovascular system. We found that an increase in the alpha-sympathetic gain, via a Hopf bifurcation, leads to sustained oscillations both in heart rate and blood pressure variables at about 0.1 Hz (Mayer waves). Similar oscillations were observed when increasing the beta-sympathetic gain or decreasing the vagal gain. Further changes of the gains, even beyond reasonable physiological values, did not reveal another bifurcation. The dynamics observed were thus either fixed point or limit cycle. Introducing respiration into the model showed entrainment between the respiration frequency and the Mayer waves.
Blood Pressure↗
Autonomic cardiovascular control in children with obstructive sleep apnea.
Autonomic cardiorespiratory control changes with sleep-wake states and is influenced by sleep-related breathing disorders. Power spectrum (PS) analysis of instantaneous fluctuations in heart rate (HR) is used to investigate the role of the autonomic nervous system (ANS) in cardiorespiratory control. The two spectral regions of interest are the low frequency component (LF) and high frequency component (HF). The aim of the present study was to investigate the autonomic cardiorespiratory control in children with obstructive sleep apnea (OSA) syndrome. We studied 10 children with OSA versus 10 normal children. All subjects underwent whole night polysomnography. Spectral analysis of the HR and breathing signals was performed for 256 second long, artifact-free epochs in each sleep-wake state. The LF power was higher in the OSA group compared with control subjects for all states, reflecting enhanced sympathetic activity in OSA subjects. The results indicated sympathetic predominance during REM sleep in all subjects and parasympathetic predominance in slow wave sleep only in controls. The autonomic balance (LF/HF) was significantly higher in OSA patients than in control subjects, at all stages during night sleep, and while awake before sleep onset. An index of overall autonomic balance (ABI) was computed for each subject and correlated well with the measured respiratory disturbance index (RDI).
Autonomic Nervous System↗
Phase response curve based model of the SA node: simulation by two-dimensional array of pacemaker cells with randomly distributed cycle lengths.
A simulation of the SA node is presented, based on a 2D array (15 x 15) model of randomly distributed pacemaker cells, interacting via a phase response curve (PRC). The model involves only the basic properties that play a direct role in the determination of the SA node rhythm: intrinsic cycle length and PRC. The PRC reflects the 'type' of interaction of each pacemaker cell with the outside world (neighbouring cells, external stimulus, etc.). A major outcome of this study is the demonstration that global dynamics and the degree of 'disorder' of the SA node are strongly affected by the cycle length distribution of the model, as well as spatial inhomogeneity in the cell-to-cell 'electrical' coupling (PRC). Those factors also determine the conduction velocity throughout the SA node and may therefore be responsible for anisotropic conduction. For example, lowering the PRC parameters (d and a) by 25% increases the array activation time from 46 to 126 ms. The model also responds appropriately to a perturbation such as a vagal pulse. This pulse produces a shift of the dominant pacemaker to another site in the array and a transient lengthening of the array cycle length, for example from 312 to 355 ms.
Biological Clocks↗
Simulation of atrial activity by a phase response curve based model of a two-dimensional pacemaker cells array: the transition from a normal activation pattern to atrial fibrillation.
In this paper, we present an original model of the atria, based on our hypothesis that atrial cells have features of pacemaker cells, characterized by their normally longer intrinsic cycle lengths and different type of connection (stronger) than the, sino-atrial (SA) node pacemaker cells. The atrium is simulated by a two-dimensional array of pacemaker cells (25 x 25), composed of a region of SA node pacemaker cells (11 x 11) surrounded by atrial pacemaker cells. All pacemakers cells are characterized by only the most relevant functional properties, those which play the most direct role in the determination of the cardiac rate and in the mechanism of arrhythmias. These properties are: the intrinsic cycle length, tau, an 'internal' feature of each pacemaker cell, and the phase-response curve (PRC), an 'overall collective' function. The PRC embodies the interactions of each pacemaker cell with its neighboring cells, and thus represents the type of connection (strong, weak, etc.) of the pacemaker cell with its surroundings. In our model, the SA node region differs from the atrial region by cycle length distribution and PRCs. We studied the spatial interaction between SA node pacemaker cells and atrial pacemaker cells as a function of the regional variation of cells properties and as a function of the "electrical" coupling between cells (the PRC), in the SA node region, in the atrial region, and in a border zone between them. We investigated the influence of those parameters on the activation pattern, on the conduction time of the array, and on a pseudo-ECG signal. This study demonstrates that by representing the atrial cells as a population of 'pacemaker-like' cells, similar to the SA node pacemaker cells, but differing markedly in their cycle lengths and cell-to-cell interaction (PRC), we can create a global picture of the atrial system by applying a simple physical-mathematical model. This approach enables us to explore physiological phenomena related to the genesis and maintenance of atrial activity. It also reveals the conditions which predispose to atrial arrhythmias and conduction disturbances (e.g. tachycardia, pacemaker shift, re-entry, fibrillation). In particular, it yields insight into the mechanism of transition from normal atrial activity to the disordered state of atrial fibrillation. Therefore, this study suggests a new way of looking at the development of cardiac arrhythmias of atrial origin.
Atrial Fibrillation↗
Computerized quantification of structures within ovarian cysts using ultrasound images.
Ovarian cysts are a common type of ovarian mass. The morphology of cysts, as it appears in ultrasound images, is currently used for classification of ovarian pathologies. However, this classification process is based on human interpretation of the sonographic image. In this article, a semiautomatic algorithm for the quantification of ovarian cysts is presented. This algorithm categorizes the structures within a cyst and extracts their quantitative geometric properties (width, characteristic diameter). To assess the validity of the technique, its performance was compared to human classification and manual measurements made by an expert. The results show a good match between automatic evaluations made by a computer and those of an experienced observer, indicating a potential for clinical use.
Algorithms↗
Application of a semiautomatic boundary detection algorithm for the assessment of amniotic fluid quantity from ultrasound images.
The aim of this study was to develop a computer-assisted method to evaluate amniotic fluid volume (AFV). This was done by automatically detecting the boundaries of the amniotic fluid portion in 2-D ultrasonographic images. The study population consisted of 36 low-risk patients that were selected at random from a healthy population undergoing routine pregnancy follow-up. For each patient, images of the four quadrants of the uterus were digitized into a PC. The amniotic fluid portion in each ultrasonographic image was automatically detected, and its area was calculated. Its area was also manually determined by an expert physician (R. T.). The areas automatically detected by the algorithm were highly correlated with the areas manually delimited by the expert: r2 = 0.9722 (p < 0.01). The areas calculated by the program provide a good measure for the areas determined by the expert and may, therefore, be used for calculating the actual amniotic fluid volume.
Algorithms↗
Correlation dimension estimation: can this nonlinear description contribute to the characterization of blood pressure control in rats?
The application of correlation dimension estimation to the study of cardiovascular control, via the blood pressure (BP) time series was investigated. We chose to calculate the Grassberger-Procaccia (GP) correlation dimension. In order to obtain a reliable estimate of the correlation dimension, we studied impact of various parameters such as the appropriate sampling rate, the time delays, the embedding dimension, the minimal trace length required, and the number of points needed as reference points. We developed a recipe for the reliable treatment of the continuous BP signal in rats, our animal model, and discussed the possible pitfalls which demand special attention. Next, we applied the surrogate data method to a BP time series, looking for the existence of nonlinear components, in order to test whether the nonlinear modeling is necessary for accurately describing the system. We found that, indeed, the correlation dimension does reveal information which cannot be unveiled by the commonly used power spectral technique, thus, making the nonlinear modeling an important approach, providing additional insight into the cardiovascular control system.
Algorithms↗
The effect of thermal stimulation on the heart-rate variability in neonates.
Thermoregulation in humans can be divided into three broad mechanisms of control, namely: shivering, sweating and vasomotor activity. Previous investigations suggested the presence of an autonomic rhythm, originating in the central nervous system, possibly related to thermal vasomotor control and directly affecting heart rate by reflex changes in cardiac sympathetic and parasympathetic activity. The objective of the present work was to study the maturation process of the thermoregulatory system in newborns. We used peripheral thermal entrainment and focused on the reflections of vasomotor control in the heart-rate (HR) power spectrum (PS). The study included three groups of neonates at three different ages: 10 premature infants, 6 full-terms and 7 older infants (4 to 6 months). Thermal stimulation was achieved by placing a hot and cold surface on the subject's right palm alternately at three different rates: replacing the touching surface every 4 s (0.25 Hz), 7 s (0.14 Hz) and 10 s (0.1 Hz). 'Double period' stimulation was defined as the total duration of each period of hot and cold stimulation at the three rates, namely 8 s (0.125 Hz), 14 s (0.07 Hz), 20 s (0.05 Hz). The ECG of every infant was measured and recorded during the various stages of the experiment. The HR power spectrum from 0.02 Hz up to 2.00 Hz was considered, focusing on narrow ranges around the thermal stimulation frequencies. We found that in most subjects, clear peaks arise in the HR PS at the thermal entrainment frequency and its corresponding half frequency ('double period'). In premature infants, the reaction is best in response to the longest (10 s) stimulus (9 out of 10 prematures reacted positively), in group B (full-term infants) the reaction responds best to the 7-s stimulus (6 out of 6 reacted) and in older infants the reaction is slightly better at the 4-s stimulus. Since sympathetic control is slower, this ability to entrain the control system at increasing frequencies, might be related to the gradual maturation of parasympathetic control after birth. The different reaction of the three groups may help to understand the maturation process of the thermoregulation system.
Adaptation, Biological↗
A phase response curve based model: effect of vagal and sympathetic stimulation and interaction on a pacemaker cell.
This study introduces a simple mathematical model for a pacemaker cell affected by an external parasympathetic and/or sympathetic input. The model presented is based on the two most important functional properties of the cardiac pacemaker cells. The first property is the intrinsic pacemaker cycle length, an "internal" parameter of the cell. The second basic property is the phase response curve (PRC), a function which reflects the various interactions of the pacemaker cell with the outside world (i.e. interaction with surrounding cells, external stimulus). The vagal stimulus is simulated as affecting the pacemaker cycle length via a PRC, while the sympathetic input is expressed in the model as a continuous reduction in the pacemaker cycle length. When combined vagal and sympathetic activation is allowed, our model shows that autonomic systems are also capable of interacting. First, we studied the entrainment phenomena resulting from a repetitively applied vagal stimulus. Various complex patterns of dynamic interaction between the pacemaker cell and the vagal input were simulated. The PRC parameters appear to be an important factor in the prediction of the entrainment phenomena. Specifically, they permit a quantitative description of the limits of a 1:1 synchronization zone. Next, we apply this model to qualitatively investigate the phenomenon of "accentuated antagonism" between parasympathetic and sympathetic autonomic branches. We examined the various options for this interaction in regulating the pacemaker periodicity. Although this model is a simplified reflection of the biological system, we conclude that it can mimic many aspects of the dynamic autonomic control and of the possible interactions between vagal and sympathetic stimulation of a pacemaker cell.
Animals↗
A PRC based model of a pacemaker cell: effect of vagal activity and investigation of the respiratory sinus arrhythmia.
In this study we present a computer model of a pacemaker cell subjected to vagal stimulation. This model allows us to investigate the entrainment phenomena of the pacemaker cell resulting from its dynamic interaction with a periodic train of vagal bursts. The possibility of entrainment depends mainly on the fact that a vagal stimulation discharge can "correct" the pacemaker rhythm by an amount that depends on its instantaneous relationship to the pacemaker cycle length. This very simple model, is based on the two most important functional properties of the cardiac pacemaker cells. The first property is the intrinsic pacemaker cycle length, which is an "internal" parameter of the cell, describing the most basic feature of a pacemaker cell. The second one is the phase response curve (PRC), which is an "overall collective" function, containing all the "information" about the possible interactions between the pacemaker cell and the outside world (i.e. its interaction with surrounding cells, external stimulus, etc.). A "collective" PRC was reconstructed from the resulting effects of all the pulses composing a burst. It appears that the PRC parameters as well as the vagal burst parameters are important factors in predicting the entrainment phenomena. Specifically, we found that the tendency of the pacemaker cell to become synchronized with bursts of vagal activity is greater, the larger the number of pulses per burst. However, increasing the number of pulses may also increase the tendency of the pacemaker towards instability, which was unveiled as changes in the configuration of the "collective" PRC. We applied the periodic train of vagal bursts so as to simulate the respiratory sinus arrhythmia (RSA) modulation on the pacemaker cell. We included also a modulation of sympathetic origin, represented as periodic changes in the intrinsic pacemaker cycle length. The frequency response of the pacemaker to "autonomic" modulations allowed us to demonstrate that the RSA dynamics can be interpreted in terms of the entrainment of the pacemaker cell by the respiratory modulation of vagal activity.
Autonomic Nervous System↗
Mapping strain exerted on blood vessel walls using deuterium double-quantum-filtered MRI.
A technique is described for displaying distinct tissue layers of large blood vessel walls as well as measuring their mechanical strain. The technique is based on deuterium double-quantum-filtered (DQF) spectroscopic imaging. The effectiveness of the double-quantum filtration in suppressing the signal of bulk water is demonstrated on a phantom consisting of rat tail tendon fibers. Only intrafibrillar water is displayed, excluding all other signals of water molecules that reorient isotropically. One- and two-dimensional spectroscopic imaging of bovine aorta and coronary arteries show the characteristic DQF spectrum of each of the tissue layers. This property is used to obtain separate images of the outer layer, the tunica adventitia, or the intermediate layer, the tunica media, or both. To visualize the effect of elongation, the average residual quadrupole splitting is calculated for each pixel. Two-dimensional deuterium quadrupolar splitting images are obtained for a fully relaxed and a 55% elongated sample of bovine coronary artery. These images indicate that the strong effect of strain is associated with water molecules in the tunica adventitia whereas the DQF NMR signal of water in the tunica media is apparently strain-insensitive. After appropriate calibration, these average quadrupolar splitting images can be interpreted as strain maps.
Animals↗
Beat-to-beat fluctuations in the BP related signals in rats: can it contribute to the understanding of the development of hypertension?
The goal of this study was to investigate the alterations in blood pressure control in young spontaneously hypertensive rats (SHR), as reflected in the power distribution of blood pressure fluctuations. We studied six SHR preceding the onset of overt hypertension, compared to six age matched control rats, the normotensive Wistar-Kyoto rats (WKY), and analyzed the power density distribution of several blood pressure related signals, namely: arterial blood pressure (ABP), systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP) and heart rate (HR). ABP fluctuations exhibited a basic difference in the power distribution pattern between the strains: at low frequencies (< 0.15 Hz) more power was observed in WKY than in SHR, while in the (0.35-1.00 Hz) range, more power was observed in SHR. These significant differences in patterns which existed at baseline, were abolished by prazosin (2.5 mg/kg). Observing the power distribution in the BP related signals, the patterns were different from that found in the ABP itself. At baseline, in SBP and DBP, the most dominant power was located at low frequencies < 0.04 Hz, like in ABP. However, unlike ABP, the remainder of the power was located in the high frequency region (HF: 1.5-3.0 Hz), mainly in SHR. Prazosin had a marked effect on PP power spectra; it shifted the power to the HF region in both strains. In PP, power spectra differences observed between the strains at baseline in HF were eliminated by prazosin. This seems to indicate that, in SHR compared to WKY, respiratory fluctuations which are low at baseline in PP, are a mechanical reflection of the higher sympathetic tone in SHR before alpha1 sympathetic blockade. This study supports previous findings in which differences in cardiovascular control occur in SHR already at the prehypertensive stage. The above results suggest that alpha1 sympathetic control is altered in the SHR strain, and therefore, when this limb is blocked, some of the differences between the strains disappear. Furthermore, the analysis of the BP related signals enable us to identify alterations existing in the control mechanisms in SHR, which involve adjunct control mechanisms enhanced under alpha1 sympathetic blockade. Finally, an important result is, that for all BP related signals under study, excluding HR, the response to alpha1-blockade reduces the power density in the 0.07-0.15 Hz region indicating that this region is directly associated with the activity of alpha control.
Adrenergic alpha-Antagonists↗
A single pacemaker cell model based on the phase response curve.
A single pacemaker cell model and its response to repetitive external depolarization stimulations is described in this paper. This model is a simple model based on the two most important functional properties of the cardiac pacemaker cells. The first property is the intrinsic pacemaker cycle length, which is an 'internal' parameter of the cell, describing the most important feature of a pacemaker cell. The second functional property is the phase response curve (PRC), which is an 'overall collective' function: it contains all the 'information' about the possible interactions of the pacemaker cell with the outside world (external stimulus, interaction with surrounding cells, etc.). This study demonstrates that by representing the pacemaker cell only by two fundamental features, and by applying a simple physical-mathematical model, a global picture of the system can be achieved, allowing us to explore qualitatively various physiological phenomena related to the pacemaker function. For example, we demonstrated that the PRC is a crucial parameter in the prediction of the entrainment phenomena of a single pacemaker cell in response to a periodic train of depolarization pulses. Specifically, the PRC permits a quantitative determination of the 1:1 synchronization range for a single pacemaker cell and an external depolarization pulse. Moreover, we show that the PRC can be used to represent the type of external stimulus applied to the pacemaker (e.g. depolarization pulse) and its intensity. Therefore, the PRC emerges as an important determinant and a useful 'tool' for the understanding of the dynamic interaction of pacemaker cells with the outside world. As a result of our simulations, we unveil a new important parameter: the 'degree of influence', which determines the range of 1:1 synchronization between an external depolarization pulse and a pacemaker cell. This interaction parameter is a direct function of the PRC parameters. It appears to be a helpful 'tool' for the understanding of synchronization and mutual entrainment mechanisms between the pacemaker cell and an external stimulus, and therefore it supports the basic importance of the PRC in the description and determination of these mechanisms.
Animals↗
A pacemaker cell pair model based on the phase response curve.
A pacemaker cell pair model and the dynamic interaction between the two pacemaker cells is described in this paper. It is an extension of our single pacemaker cell model, in which we studied its response to repetitive external depolarization stimulations. This model is a simple model based on the two most important functional properties of the cardiac pacemaker cells: its intrinsic pacemaker cycle length, which is an 'internal' parameter of the cell, and the phase response curve (PRC), which is an 'overall collective' function. The PRC contains all the 'information' about the possible interactions of the pacemaker cell with the outside world (interaction with surrounding cells, external stimulus, etc.). First, we examined the properties and solutions of 1:1 synchronization between two pacemaker cells. We found that in order to achieve synchronization between two pacemaker cells, there should be limitations on the PRC parameters, which depend on the cells intrinsic cycle lengths. Next, we investigated the 2:1 entrainment state between two interacting pacemaker cells. We found that there is not necessarily a unique solution for this state as there was for the 1:1 state. Finally, we ran our computer model to investigate the properties of more complex patterns of entrainment between two pacemaker cells. As a result of our analytical study, we unveil two new important parameters, which are fully defined as a function of the PRC parameters: (1) the 'accelerator factor' which describes the tendency of a pair of interacting pacemaker cells to synchronize at a common cycle length, which is closer to the faster cycle of the pair; (2) the 'degree of coupling', which describes the range of the 1:1 synchronization and the 'strength' of the interaction between a pair of interacting pacemaker cells. Those two interaction parameters arise as helpful 'tools' for the understanding of synchronization and mutual entrainment mechanisms between pacemaker cells. Therefore, this study establishes the PRC as an important determinant and a useful approach for the understanding of the dynamic interaction of pacemaker cells among themselves and with the outside world.
Animals↗
Automatic assessment of cardiac function from short-axis MRI: procedure and clinical evaluation.
Cardiac magnetic resonance imaging (MRI) provides a wealth of morphological and physiological information. Automatic extraction of this information is possible by implementing various image processing techniques. However, existing procedures mostly rely on extensive human interaction and are seldom evaluated on a clinical scale. In this study, a nearly automatic process that extracts physiological parameters from cardiac MR images has been both developed and clinically evaluated. Raw images were obtained in the short-axis view and acquired by a gradient-cho (GE) protocol. In images selected to be analyzed, the only manual step required is the indication of a point in the center of the left ventricle (LV). From a set of such images, the process extracts endocardial and epicardial contours and calculates left ventricular volumes, mass and ejection fraction (EF). The process implements novel approaches to image processing techniques such as thresholding and shape extraction and can be adapted to other acquisition protocols. The process has demonstrated a clear potential for accurate extraction of the endocardial contour but a lower one with respect to the epicardial contour as a result of the low contrast between myocardium and some surrounding tissues, generated by the gradient-echo protocol. The ability of the process to asses physiological parameters has been subjected to a systematic clinical evaluation, which compared parameters, derived manually and automatically, in 10 healthy subjects and 10 patients. The evaluation has indicated that although individual volumes and mass were not accurately assessed, the automatic process has shown high potential for assessing the ejection fraction with relatively high accuracy and reliability.
Adult↗